Jintang Li

Awesome-Masked-Autoencoders. A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).

Graph-Adversarial-Learning. A curated collection of adversarial attack and defense on graph data.

Awesome-Learning-Resource. A curated list of all kinds of learning resources, blogs, books, videos and so on.

GraphGallery. GraphGallery is a gallery for benchmarking Graph Neural Networks

Awesome-Fair-Graph-Learning. Paper List for Fair Graph Learning (FairGL).

RS-Adversarial-Learning. A curated collection of adversarial attack and defense on recommender systems.

ICLR2023-OpenReviewData. ICLR 2023 Paper submission analysis from https://openreview.net/group?id=ICLR.cc/2023/Conference

MaskGAE. [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders

GreatX. A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).

ICLR2022-OpenReviewData. ICLR 2022 Paper submission trend analysis from https://openreview.net/group?id=ICLR.cc/2022/Conference

SpikeNet. [AAAI 2023] Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks

ICDM2022_competition_3rd_place_solution. 3rd place solution of ICDM 2022 Risk Commodities Detection on Large-Scale E-Commence Graphs

GraphData. A collection of graph data used for semi-supervised node classification.

SpikeGCL. [ICLR 2024] Official implementation of Spiking Graph Contrastive Learning (0️⃣1️⃣ SpikeGCL)

DCIC-2023-Solution. DCIC2023 Fraud Risk Identification Competition Solution.

MAGI. [KDD 2024] Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective

GraphSSM. [NeurIPS 2024] State Space Models on Temporal Graphs: A First-Principles Study

arxiv-daily. arxiv-daily

Hetero2Net. Python

SGAttack. Official Repository for "Adversarial Attack on Large Scale Graph." [TKDE 2021]

GUARD. [CIKM 2023] GUARD: Graph Universal Adversarial Defense

STEP. Python

SAT. Python

lrGAE. A comprehensive (masked) graph autoencoders benchmark.

Mooon. Graph Data Augmentation Library for PyTorch Geometric

MedianGCN. Official PyTorch implementation of MedianGCN and TrimmedGCN in Understanding Structural Vulnerability in Graph Convolutional Networks (IJCAI 2021).

CIKM22_FL_Competition. 4th place (4/1746) solution of CIKM 2022 AnalytiCup Competition.

BlockGCL. PyTorch implementation of Blockwise Graph Contrastive Learning (BlockGCL)

EdisonLeeeee.github.io. Github pages

GraphAdv. TensorFlow 2 implementation of state-of-the-arts graph adversarial attack and defense models (methods).

SGC_tf2.0. Python implement of SGC with Tensorflow 2.0.

KDDcup24-AQA. Jupyter Notebook

Introduction_to_graph_adversarial_learning. An introduction to graph adversarial learning

EdisonLeeeee.

TemporalDatasets.

glcore. graph learing toolbox

starter-hugo-academic. Jupyter Notebook